Short abstract:

Smart home devices impact home's ethical norms but developers may lack methods and experience to consider ethics during innovation. We develop a collaborative, transdisciplinary methodology to embed upstream ethical reflection in industry contexts that may have value beyond the smart home milieu.

Long abstract:

Smart home devices have become a popular new technology and include smart TVs, kitchen appliances, lighting systems and security cameras. However, these devices have generated significant concerns about privacy and related ethical issues such as autonomy and respect (Lund, 2014; Lau et al, 2018). To prevent such ethical harms, developers are encouraged to perform upstream reflection. Some smart home researchers have used sociological research to produce normative data on the experiences of living with smart home devices (Kraemer & Flechais, 2018; Chalhoub et al, 2021). Yet most smart home device development occurs in industry contexts by technology developers who may not be familiar with or have the expertise to conduct ethical reflection. In response, we draw on the established ‘N-Reasons’ applied ethics survey tool (Danielson, 2013) and further develop it as a transdisciplinary and collaborative methodology capable for use in an industrial context. We map our co-development of this tool in collaboration with industry practitioners to assess ethically complex human and human-robot-interaction scenarios. We show how the tool helps to identify which home privacy norms are affected by smartness, and how smart device perceptions are socially generated by users and non-users. We demonstrate that the tool offers a novel transdisciplinary approach for embedding ethical reflection upstream in industry contexts that may have value beyond the smart home device milieu.

Short abstract:

Museums are implementing collaborative methods, like involving users in the development of technologies. Such Co-design processes raise questions about the translation of IT specifics. Our contribution focuses on the challenges, limits, and potentials of our role as ethnographers in such processes.

Long abstract:

Museums as important mediators of knowledge are currently undergoing transformations towards implementing digital technologies in their work. In line with the formulated aim of new museology, museums aim at opening up and further democratizing their knowledge transfer (Fleming 2002, Benett 1995). In this process, digital technologies are intended to become a tool for broadening up and actively including audiences (Runnel & Pruulmann-Vengerfeldt 2014). Collaborative design methods, like involving users in the development of such technologies, for example, apps, are gaining popularity as forms of visitor participation, as our research suggests. Yet, the degree of collaboration can vary greatly and is often related to the willingness of institutions to share their interpretative power with the co-developers and audiences. Co-design processes also raise questions about the translation and communication of IT specifics. Can ethnographers in this context function as mediators between developers and users? What mutual learning processes arise from the co-laborative app development and digital transformation of museums? Drawing on experiences from two research projects, our contribution reflexively focuses on the challenges, limits, and potentials of our role. Whereas the project “Challenging Populist Truth-Making in Europe” (CHAPTER) co-develops an app that is more of an intervention within museums, the second case of the ARTifacts app by Deutsches Schifffahrtsmuseum involves school classes as actors. In both cases, different motives and demands of the actors involved meet, and we as ethnographers contribute to translation processes, experiencing mutual learning processes: as researchers, observers, and mediators.

Short abstract:

The digital transformation of healthcare requires interdisciplinary col-laboration and participatory involvement of stakeholders from diverse, sometimes vulnerable groups through co-creation. This collaboration offers opportunities and challenges, illustrated by two interview studies' results.

Long abstract:

The starting point for the presentation are co-laborations in interdisciplinary and interprofessional technology development projects (TDP) that each develop hybrid health technologies. The aims of participation in TDP are to develop technologies that adapt well to the users' living environments, meet their needs, or change or improve social practices. An important factor is the exchange between the disciplines and professions and the willingness to learn together to implement participatory formats.

As part of an accompanying research project (AP), group interviews have been conducted with TDP. Among others, the conditions for the success of interdisciplinary and interprofessional collaboration (ICD) as well as heterogeneous understandings of participation were discussed. The AP (social informatics, UX research, co-creation, care, gerontology) accompanies the TDP and consults on participatory methods, for example.

Based on the results of the interviews (e.g., finding a common language, dealing with prejudices, heterogeneous goals, heterogeneous understandings of participation) and the experiences of a reflective accompaniment through the AP, a use has been developed. The following questions will be discussed: 1) Is the interdisciplinarity and interprofessionality of the TDP a pitfall or a prerequisite in the context of participatory technology development? 2) How can a common understanding of participation be negotiated within the TDP in order to facilitate the design of participatory formats? 3) What role can the reflective support provided by the AP play here? The interactive contribution includes the presentation of a podcast in which the use case is discussed from social science, socio-technical and technological perspectives.

Short abstract:

We introduce the constellation analysis as a concept for transdisciplinary exchange and present evidence from our research project Uckerbots. The mapped constellation illustrates compiled knowledge on the potential of robotic weed control.

Long abstract:

Co-design and transdisciplinary approaches are supposed to help tackling complex challenges in agriculture, for instance by enabling knowledge exchange and joint learning (Busse et al., 2019; Hölting et al., 2022; van Ewijk and Ros-Tonen, 2021). In practice, the question arises how a transdisciplinary exchange can accomplish these positive outcomes. We introduce the constellation analysis (CA) as a bridging concept to conflate knowledge of actors with distinctive perspectives (Schäfer and Kröger, 2016; Schön et al., 2007). CA is inspired by actor-network theory and visualizes actors, elements and their relations in order to stimulate a mutual understanding between social actors.

We present evidence from our project Uckerbots, in which an agritech start-up, agricultural and social scientists, farmers and IT specialists collaborate to develop a weeding robot for sugar beet cultivation and to create a sustainable value chain in north-eastern Germany. Our CA illustrates the status quo of organic sugar beet cultivation in north-east Germany and a possible future constellation with robotic weed control. We have iteratively developed the constellations based on feedback of the different project partners and further important regional actors (e.g. employee of the regional sugar company). The creation of the CA brings together the different perspectives of technology development, sugar beet cultivation and weed removal, and captures social and cultural aspects related to the establishment of the technology. It fosters a common problem understanding between the involved scientists and practitioners. The knowledge gained from the CA will be utilized for the development of a suitable business model.

Literature

Busse, M., Siebert, R., Heitepriem, N., 2019. Acceptability of innovative biomass heating plants in a German case study-a contribution to cultural landscape management and local energy supply. Energy Sustainability and Society 9, 36. https://doi.org/10.1186/s13705-019-0215-2

Hölting, L., Busse, M., Bülow, S., Engler, J.O., Hagemann, N., Joormann, I., Kernecker, M.L., Larondelle, N., Sturm, A., Turkelboom, F.,

Wätzold, F., Cord, A.F., 2022. Co‐design: Working with farmers in Europe to halt the loss of biological diversity. Ecol Sol and Evidence 3, e12169. https://doi.org/10.1002/2688-8319.12169

Schäfer, M., Kröger, M., 2016. Joint problem framing in sustainable land use research: Experience with Constellation Analysis as a method for inter- and transdisciplinary knowledge integration. Land Use Policy 57, 526–539. https://doi.org/10.1016/j.landusepol.2016.06.013

Schön, S., Kruse, S., Meister, M., Nölting, B., Ohlhorst, D., 2007. Handbuch Konstellationsanalyse: ein interdisziplinäres Brückenkonzept für die Nachhaltigkeits-, Technik- und Innovationsforschung. oekom verlag GmbH, München.

van Ewijk, E., Ros-Tonen, M.A.F., 2021. The fruits of knowledge co-creation in agriculture and food-related multi-stakeholder platforms in sub-Saharan Africa – A systematic literature review. Agricultural Systems 186, 102949. https://doi.org/10.1016/j.agsy.2020.102949

Short abstract:

This paper reflects on the epistemological and methodological challenges of conceptualizing ‘ground truths’ and the sociomaterial practices of producing and annotating ethnographically-informed datasets for social media analysis in an interdisciplinary setting.

Long abstract:

Beauty standards and image-based social media intricately shape the aesthetic regimes of platforms, and therefore, how users perceive and represent themselves online. The interdisciplinary project "Curating the Feed" investigates how the socio-technical entanglements of digital practices, user interfaces, and algorithmic systems co-curate image feeds on social media platforms like Instagram or TikTok. Our ongoing collaboration between cultural anthropology and computer science involves developing a machine learning system that classifies posts in image feeds to determine whether posts are perceived as perpetuating idealized notions of beauty. In order to indirectly approximate the ‘blackboxed’ recommender systems of the home feed, we aim to evaluate the one-sidedness of image feeds and experiment with algorithmic intervention as well as ethnographic methods. This paper reflects on the epistemological and methodological challenges of conceptualizing ‘ground truths’ and the sociomaterial practices of producing and annotating datasets for social media analysis in an interdisciplinary setting. Building on the concept of ‘ground truth tracings’ (Kang 2023), we address the collaborative effort to construct and translate a qualitative phenomenon into a quantitative formalization. Drawing on critical dataset studies, we furthermore explore how ethnographic methods can be utilized to aid the calls for more transparency and reflexivity. By exploring the ML system’s ‘learnability’ to classify content with regards to idealized representations of bodies, this research aims to contribute to debates about algorithmic bias and transparency as well as the adaptability of ethnographic methods.

Short abstract:

The contribution aims to explore the role of qualitative research methods in research software engineering with a focus on contextual inquiry as a collaborative approach of user-centric research software engineering specifically. It draws from a PhD research project that makes use of the approach.

Long abstract:

As our research processes become more digital under the paradigm of open research and open data, there is an increased demand for research software tailored to support these processes (RfII 2023). Even though software engineering has traditionally relied upon methodologies from the fields of humanities and social sciences in steps in the software development process such as requirement elicitation and usability research (Dybå et al 2011), researchers from these fields are largely underrepresented in the area of research software engineering (RSE, Philippe et al 2019). As a collaborative user-centric approach, contextual inquiry (CI, Raven and Flanders 1996) not only incorporates methodologies from humanities and social sciences, if applied to RSE, it allows researchers from these fields to play an integral part in developing specific research software.

This contribution aims to explore the role of qualitative research methods in RSE generally, and CI as a collaborative approach of user-centric RSE specifically. It draws from an ongoing PhD research project that in itself makes use of CI within RSE in digital humanities and qualitative research processes.

References:

RfII. (2023). RfII-Bericht „Föderierte Dateninfrastrukturen für die wissenschaftliche Nutzung“.

Dybå, Prikladnicki, Rönkkö, Seaman, Sillito, (2011). Qualitative research in software engineering. 425-429.

Raven, Flanders, A. (1996). Using contextual inquiry. 1-13.

Philippe, Hammitzsch, Janosch, van der Walt, van Werkhoven, Hettrick, Katz, Leinweber, Gesing, Druskat, Henwwergood, May, Lohani, Sinha, (2019). Softwaresaved/international-survey (2018-v.1.0.2).

Short abstract:

The paper presents reflections and interim results of ongoing interdisciplinary research on presumptions and foundations of human control of AI. The “AI-Cockpit” is a research project aimed at building an interface that grants humans oversight and control over systems of automated decision making.

Long abstract:

Within the framework of the project “AI-Cockpit”, a technology for an AI-system-interface will be developed that enables both human oversight and control over the automated decisions of various AI-systems. Our interdisciplinary research team is thus faced with the challenge to further conceptionalize the idea of “Human in Command of AI” and at the same time generate practical implementations of our premise. We follow a human-centered research approach using participatory methods. In addition, we will develop a generic “cockpit model” that can be used across individual cases and in the design of new AI-systems. Our approach is strictly aligned with the requirements of the EU-AI Act.

In three different application areas (Human Resources, Smart City, Care), first prototypes will be developed which provide insights across the individual areas and enable the development of free/libre open-source software. Our research network is composed of computer scientists, Industrial and organizational psychologists, STS scholars, cultural anthropologists and neuroscientists who in cooperation with our practice partners contribute to the design of a cockpit model.

For our project we have chosen a special variant of interdisciplinary work: Our synthesis-based-research project is accompanied by practitioners who make their own significant contribution to the research. In all fields of application, we go beyond general interdisciplinary cooperation and ask people in the respective fields about their needs, their experiences and assessments in terms of sustainable cooperation (vgl. Klausner/Niewöhner 2020, 163). This creates "epistemic partnerships" (Bieler et al. 2021, 525) which promise added value in the development of human-centered AI systems.